Industrial Robot
Industrial robots are increasingly central to manufacturing, with research focusing on improving their safety, efficiency, and human-robot collaboration. Current efforts concentrate on developing more intuitive and adaptable robot control systems, including human-like kinematic models and real-time adaptive systems that respond to operator physiological signals, often employing machine learning algorithms like Bayesian optimization and deep reinforcement learning for improved performance and safety. These advancements aim to enhance productivity, worker comfort and safety, and the overall integration of robots into diverse industrial settings.
Papers
Applying PBL in the Development and Modeling of kinematics for Robotic Manipulators with Interdisciplinarity between Computer-Assisted Project, Robotics, and Microcontrollers
Afonso Henriques Fontes Neto Segundo, Joel Sotero da Cunha Neto, Paulo Cirillo Souza Barbosa, Raul Fontenele Santana
Development of a robotic manipulator: Applying interdisciplinarity in Computer Assister Project, Microcontrollers and Industrial Robotics
Afonso Henriques Fontes Neto Segundo, Joel Sotero da Cunha Neto, Reginaldo Florencio da Silva, Paulo Cirillo Souza Barbosa, Raul Fontenele Santana
Aplica\c{c}\~ao de ros como ferramenta de ensino a rob\'otica / using ros as a robotics teaching tool
Daniel Maia Evangelista, Pedro Benevides Cavalcante, Afonso Henriques Fontes Neto Segundo